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The Hitchhikers Guide to Soumen Chakrabarti Faculty Advisor.

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Presentation on theme: "The Hitchhikers Guide to Soumen Chakrabarti Faculty Advisor."— Presentation transcript:

1 The Hitchhikers Guide to MTech@CSE@IITB Soumen Chakrabarti Faculty Advisor

2 2 The big picture, first year  Semester 1 (Fall 2006) 3 Elective courses (3*6 credits) Software Lab (4 credits) Seminar (4 credits) Communication skills (pass/fail)  Semester 2 (Spring 2007) Mood Indigo, Tech Fest, PAF, … 4 Electives (4*6 credits), mini-project? 1 Institute elective (6 credits) Fix MTech projects (MTP) by approx middle of semester Major Time Pass Heavy! Need discipline, time management

3 3  Summer 2007 MTP1 (22 credits) viva end of July  Semester 3 (Fall 2007) 2 Elective courses (2*6 credits) MTP2 (28 credits) Pre-placement, interviews,…  Semester 4 (Spring 2008) Mood Indigo, Tech Fest, PAF, … MTP3 (40 credits) viva mid-end July  MTP: 90 credits, courses: ~68  Minimum CC grade to remain in program If this is not keeping you busy, you are in trouble The big picture, second year

4 4 Lifelines: Do not hesitate to…  Look foolish if necessary Can’t beat your faculty advisor at that!  Ask for help Solve the problem vs. appear more self-reliant  Give your best (your finest years!)  Be honest with everyone, all the time  Demand that academics be fun  Eat well, sleep 7h, exercise, no matter what  Make friends, balance work and life  Develop long-term interests and career goals

5 5 Facilities  Carry your ID card with you at all times  CSE: labs, servers, accounts, classrooms At the moment spread across many buildings HQ in EE annex, lectures in Math and KReSIT, some groups in Math basement  Computer Center (“CC”) Institute-level accounts, access, software, email, file server etc.  Other meeting places for coursework P. C. Saxena Auditorium (a.k.a. “LT”), Girish Gaitonde (“GG”) building, “convo hall”  “Main Building” for administrative paperwork

6 6 Registration  CC has given you “LDAP” login Ids Course registration, personal data update, IIT’s central Web proxies, email routing  Right now, some faculty members will describe their research areas and courses they teach  After that, you will use your CC-assigned logins to register for courses CSE does not have formal “specializations” You probably want to pick 1—2 target areas informally

7 7 Which courses?  Generally MTech/PhD students pick “CS6xx” or “CS7xx” courses  Can also take IT6xx, IT7xx, EE6xx, EE7xx  But if you are keen on taking a “CS4xx” course talk to the instructor  A course runs in a “slot” that determines lecture hours and exam times  Cannot enroll for more than one course in any slot 

8 8 Seminar and project allocation  Faculty members publish topics and short descriptions  Students express preferences, talk to faculty members  First round of matching based on preference  Completed at some deadline  “Forced matching” for the rest soon after  Students may benefit from continuity from seminar to project  But not required by dept policy

9 9 Some CSE courses this semester  Some courses have prerequisites  Some lectures are in the evening  Also check for KReSIT, EE course offerings  Deadline for add/drop/mod 4 AUG

10 10 Broad areas (incomplete)  AI, machine learning, data mining pb, gn, soumen  Operating systems, performance analysis dmd, varsha  Databases and information management krithi, sudarsha, nls, soumen  Formal verification supratik, siva, krishnas  Graphics, computer vision sharat, sohoni

11 11 Broad areas (still incomplete)  Natural language processing pb  Networking and Internet technologies siva, varsha, krithi, soumen  Programming languages, compilers, object oriented languages uday, as, sb, dmd, rkj  Theoretical computer science sundar, aad, ranade, sohoni, ketan

12 12 Tentative schedule

13 Intro to specific faculty members

14 14 Pushpak Bhattacharyya  Areas of research Natural language processing, machine translation, machine learning, information extraction  Course this semester CS623 (Intro to Neural Nets)  Projects Lab for Intelligent Systems Cross Language Information Retrieval and Machine Translation  Lab: CFILT (Math basement)

15 15 Soumen Chakrabarti  CS705 in Autumn – Statistical foundations of machine learning (Mtech1 encouraged!)  CS610 in Spring – Web search and mining (depends significantly on CS705)  Searching using types and relations Searching in entity-relation graphs (with Prof. Sudarshan), learning ranking functions, models for text and the Web graph  Web monitoring and page analysis for mobile networks (with Prof. Ramamritham) Semi-connected Web view tuned to user profiles

16 16 Krithi Ramamritham  Course this semester: IT625, Information and Communication Technologies For Socio- Economic Development  Research areas Query processing and communication in sensor networks Monitoring dynamic content (structured and textual) through unreliable networks Databases for hand-held devices that use flash memory  Labs/Projects: Developmental Informatics Lab, Lab for Intelligent Systems, …

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