Skip to main content
UploadLanguage (EN)Support
BusinessMobileSocial MediaMarketingTechnologyArt & PhotosCareerDesignEducationPresentations & Public SpeakingGovernment & NonprofitHealthcareInternetLawLeadership & ManagementAutomotiveEngineeringSoftwareRecruiting & HRRetailSalesServicesScienceSmall Business & EntrepreneurshipFoodEnvironmentEconomy & FinanceData & AnalyticsInvestor RelationsSportsSpiritualNews & PoliticsTravelSelf ImprovementReal EstateEntertainment & HumorHealth & MedicineDevices & HardwareLifestyle
Uploaded byKhushaliDeulkar1
PPTX, PDF247 views

Research_Roadmap_for_Engineering_Students.pptx

How to select a paper, read a paper, doing literature review and publish.

Engineering◦
Downloaded 10 times
The Research Roadmap From your first problem statement to a publication-ready paper
OVERVIEW Your Research Journey, in Nine Phases 1 Discover Find a problem worth solving 2 Explore Gather resources and literature 3 Validate Confirm the problem is worth pursuing 4 Read Skim fast, then read the strong ones deeply 5 Review Take structured notes across papers 6 Design Plan your hypothesis and methodology 7 Build Implement carefully and reproducibly 8 Evaluate Judge whether your results actually hold up 9 Publish Turn results into a proper paper THE RESEARCH ROADMAP 2 / 22
MINDSET Research Is a Different Game Before the how-to, understand what changes when you move from coursework to research COURSEWORK The problem is already defined for you A correct answer already exists somewhere Success means matching the expected answer Timelines are fixed, short, and predictable RESEARCH You define the problem yourself, from scratch The answer may not exist yet, anywhere Success means new, defensible knowledge Timelines are open-ended and iterative THE RESEARCH ROADMAP 3 / 22
PHASE 1 · DISCOVER Where Problem Statements Come From A good problem rarely appears out of nowhere. It usually comes from one of these five places 1 Gaps in your coursework A topic your professor covered in one lecture, with real unanswered questions sitting just underneath it 2 Lab works/ Competitions like SIH, Kaggle etc. Ask a professor what open questions remain in their current project. Every active project has loose ends. 3 Open-source issues Unsolved bugs or feature requests on GitHub repos in your field often point to real, unsolved problems 4 Industry pain points Talk to practitioners about tasks that are still slow, manual, or unreliable in their day-to-day work 5 Replication attempts Try to reproduce a recent paper's result yourself, and pay close attention to exactly where it breaks THE RESEARCH ROADMAP 4 / 22
PHASE 1 · DISCOVER Narrowing a Broad Interest into a Question Every strong research question passes through the same funnel D O M A I N Artificial Intelligence S U BA R E A Large Language Models G A P LLMs answer confidently even when they are wrong QU E S T I ON Can a lightweight verifier catch hallucinations before an answer reaches the user? A good research question is specific enough to test in a single project and narrow enough that you can state it in one sentence. THE RESEARCH ROADMAP 5 / 22
PHASE 2 · EXPLORE Where to Search for Literature Google Scholar, Research Gate Broadest search, citation counts, and a "cited by" link on every result arXiv Preprints, including the newest work in your field, months before formal peer review IEEE Xplore / ACM DL Peer-reviewed engineering and computer science papers, the standard venues in most fields Semantic Scholar AI-assisted search that highlights which citations were genuinely influential Papers with Code Links papers directly to their code and reported benchmark results Tip: For Paywalled Papers, you can use Reddit Forums (or simply ask the authors if they can help) ;) THE RESEARCH ROADMAP 6 / 22
PHASE 2 · EXPLORE Tools That Make This Easier Reference managers Mendeley, Zotero, EndNote — organize PDFs and auto-generate citations in any format Literature mapping Connected Papers, ResearchRabbit — visualize how papers cite and relate to one another AI research assistants Elicit, Consensus, scite.ai — ask a question across many papers and see how a claim holds up elsewhere General AI assistants Tools like Claude or ChatGPT — good for summarizing dense sections and explaining unfamiliar terms, but always verify the specifics yourself Writing & collaboration Overleaf, Grammarly — collaborative LaTeX writing, plus a grammar and clarity pass before you submit THE RESEARCH ROADMAP 7 / 22
PHASE 2 · EXPLORE Snowballing: Following the Citation Trail Do this for your two or three strongest papers, and your reading list grows itself BACKWARD Check the reference list of a strong paper for the foundational work it builds on YOUR SEED PAPER FORWARD Use "cited by" to find newer papers that build on or challenge this one Backward citation chaining shows you where the ideas came from. Forward citation chaining shows you whether the problem is still open today, or whether someone already solved it after this paper was published. THE RESEARCH ROADMAP 8 / 22
PHASE 3 · VALIDATE Is This Actually a Good Problem? Run every candidate problem through this checklist before committing months to it 1 Novelty Has this exact problem already been solved well by someone else? 2 Feasibility Can you realistically build and test this within your timeline and resources? 3 Impact Does solving it matter to someone beyond just your grade? 4 Scope Can you state it in one sentence, without needing an "and" in the middle? 5 Evidence Do at least two independent sources confirm that this gap genuinely exists? THE RESEARCH ROADMAP 9 / 22
PHASE 4 · READ The Skim Test: Triage Before You Commit Give every new paper five to ten minutes before deciding whether it deserves a full read Title & Abstract Section Headings Figures & Captions Conclusion Rule of thumb: if you cannot state the paper's contribution in one sentence after this, it is not ready for a full read yet. KEEP Contribution is clear and directly relevant. Move to the three-pass method next. MAYBE Relevant but not central. Bookmark it and come back if your direction shifts. DISCARD Different problem, weak venue, or already superseded. Skip it entirely. THE RESEARCH ROADMAP 10 / 22
PHASE 4 · READ The Three-Pass Reading Method Use this only on papers that already cleared the skim test Pass Time What you do Pass 1 ~10 minutes Read the title, abstract, introduction, headings, and conclusion. Decide relevance only Pass 2 ~1 hour Read the body, study every figure and table, note key references. Skip proofs and derivations for now Pass 3 2 to 4 hours Re-derive the results yourself, question every assumption, and note what you would do differently Note: most papers you skim will never reach Pass 3, and that is expected. Reserve Pass 3 for the handful of papers your own work will directly build on. THE RESEARCH ROADMAP 11 / 22
PHASE 5 · REVIEW Keep a Running Literature Notes Table Paper Problem Method Result Limitation Relevance Paper A Object detection in clutter CNN with attention +4% mAP over baseline Never tested in real time Baseline for my comparison Paper B Path planning near people Sampling-based planner Lower collision rate Assumes static obstacles Directly motivates my gap Paper C Sensor fusion for odometry Kalman filter + IMU Reduced drift over distance Needs precise calibration Useful for my pipeline Why it matters: this table also reveals exactly where the real gap sits, since the pattern across the Limitation column is usually your research question. THE RESEARCH ROADMAP 12 / 22
PHASE 6 · DESIGN Designing Your Approach Before You Build Decide these four things on paper, before writing a single line of code 1 State a testable hypothesis Write a claim you can prove false, not just a vague goal like "improve performance" 2 Choose your baselines first Decide what you're comparing against before you build anything, not after your method already works 3 Fix your evaluation metrics Pick the numbers that will decide success up front, so you cannot quietly shift the goalposts later 4 Sketch the experiment design Note what varies, what stays fixed, and how many trials each condition needs THE RESEARCH ROADMAP 13 / 22
PHASE 7 · BUILD Implementation Practices Worth the Discipline 1 Version control everything Commit even small experiments, so you can always trace back to what actually produced a result 2 Keep code modular One component should change without breaking every other part of your pipeline 3 Log every experiment Record the parameters and full result, not just the one final number you were hoping for 4 Document setup as you go Write down each step while you remember it, not weeks later when you have forgotten why 5 Separate raw and processed data Keep both saved and clearly labeled, so you can always regenerate results from scratch THE RESEARCH ROADMAP 14 / 22
PHASE 7 · BUILD Common Implementation Pitfalls Each of these quietly invalidates a result, without ever throwing an error 1 Data leakage Testing on the same data that was used for tuning, even indirectly 2 A single lucky run Reporting one run's number instead of an average across multiple seeds 3 Skipped baselines Assuming your method "obviously" wins, so a real comparison never gets built 4 Skipped ablations Never isolating which part of your method is actually doing the work 5 Multiple variables at once Changing more than one thing between two runs you're comparing THE RESEARCH ROADMAP 15 / 22
PHASE 8 · EVALUATE Are Your Results Actually Useful? A number that looks good is not the same as a result that means something 1 Statistically significant Not just numerically higher on one run, but reliably better across repetitions 2 Beats a real baseline Compared against a serious existing method, not a deliberately weak strawman 3 Ablations isolate the contribution You can say exactly which part of your method is responsible for the gain 4 Holds up across settings Consistent across multiple seeds, datasets, or conditions, not a single favorable run 5 Passes basic sanity checks Fails gracefully on edge cases instead of silently producing nonsense A well-documented negative result, rigorously obtained, is still a valid and publishable contribution. THE RESEARCH ROADMAP 16 / 22
PHASE 9 · PUBLISH The Anatomy of a Publication-Level Paper This is the shape nearly every paper takes. Follow it unless your venue specifies otherwise 1 Abstract 2 Intro- duction 3 Related Work 4 Method- ology 5 Experi- ments 6 Results & Discussion 7 Conclu- sion 8 Refer- ences Why the order matters: Related Work comes before Methodology, so the reader understands the gap before you claim to fill it. Results and Discussion stay separate, so what happened is never confused with what it means. Some venues merge Results and Discussion or place Related Work after the Introduction instead. Always check your target venue's own template first. THE RESEARCH ROADMAP 17 / 22
PHASE 9 · PUBLISH What Actually Goes in Each Section A one-line brief for each part of the paper Section What goes here Abstract One paragraph: the problem, your approach, and the key result, in that order Introduction The motivation, the gap, and your contribution stated as an explicit list Related Work Grouped by approach rather than chronology, ending in what's still missing Methodology Enough detail that someone else could rebuild your method from this alone Experiments Setup, datasets, baselines, and metrics, described before any results appear Results & Discussion What happened, then separately, what it means Conclusion The contribution and its limits restated. No new claims introduced here THE RESEARCH ROADMAP 18 / 22
PHASE 9 · PUBLISH Writing Style That Reads Like Research DO ✓ Use active voice for your own actions: "We evaluate..." ✓ State exact numbers, not vague terms like "much better" ✓ Define every symbol and acronym the first time it appears ✓ Keep one idea per sentence AVOID ✕ Overclaiming beyond what your data actually supports ✕ Repeating the abstract's exact wording in the introduction ✕ Introducing a new term for a concept you already named ✕ Filler phrases that add words but no information THE RESEARCH ROADMAP 19 / 22
PHASE 9 · PUBLISH Choosing a Format and a Venue Check your target venue's own template and page limit before you start writing Template Layout Typical length IEEE conference Two-column 6 to 8 pages ACM conference Two-column 6 to 10 pages Springer Single-column 12 to 15 pages 1 Conferences vs. journals Conferences move fast with one hard deadline. Journals move slower but allow rounds of revision 2 Template first Page limits and formatting rules vary by venue, so confirm them before you begin writing, not after THE RESEARCH ROADMAP 20 / 22
PHASE 9 · PUBLISH Not All Venues Are Equal In computer science and AI, top conferences often outrank journals, unlike most other fields 1 Workshop / Symposium Low barrier, fast feedback 2 Regional Conference Peer-reviewed, moderate rate 3 Flagship Conference Highly selective, the gold standard 4 High-Impact Journal (Q1) Multi-round review process RANKINGS WORTH KNOWING 1 CORE Rankings CS conferences are graded A*, A, B, or C on the CORE portal. A* is the most competitive tier 2 Google Scholar h5-index Ranks venues by the citation count of their most-cited recent papers, visible under Google Scholar Metrics 3 Journal Quartiles (Q1–Q4) Based on citation-weighted scores like SJR or Impact Factor. Q1 is the top 25% of journals in a subject area A paper at a flagship venue like NeurIPS or CVPR usually counts for more than one in an average journal. This is the reverse of fields like biology or chemistry, where journals dominate. THE RESEARCH ROADMAP 21 / 22
B EF O R E YO U G O Five Things Worth Remembering 1 A good problem is specific, feasible, and confirmed by more than one source 2 Skim before you read, and read before you build 3 Document as you go. You will not remember your reasoning three weeks later 4 A rigorous negative result beats an exaggerated positive one 5 Publication is the last step of the process, not a separate skill bolted on at the end THE RESEARCH ROADMAP 22 / 22